iceDQ Platform Overview

End-to-end data reliability platform for enterprises

What is iceDQ?

iceDQ is a purpose-built platform with integrated data testing, data monitoring and AI based data observability capabilities.

iceDQ is the only platform that works across the entire data development lifecycle – development, QA, and production – ensuring robust data processes and reliable data.

OVERVIEW

Data Testing

Test the ETL data pipelines, BI reports and certify the data migrations before deploying into production.
Data Monitoring

Monitor the input data and data process when the data pipeline is running in production.
Data Observability

Use AI to automatically detect, analyze and report data anomalies.
Scheduler

Trigger rules and workflows based on a time-based schedule.
Connectors

150+ connectors for database, data lakes, document DBs, and file type such as JSON, XML, Parquet, and more.
Integrations

20+ integration for test case, and incident management tools such as JIRA, Xray test management, Azure test plans, ServiceNow, and more.
Dashboard & Reporting

Visualize pre-built DQ dashboards.

HOW IT WORKS?

KEY BENEFITS

	GRC - Governance, Risk and Compliance		Improved risk management with accurate data identification, effective data controls, and enhanced incident response. Achieve stronger regulatory compliance, accurate reporting and reduced compliance costs.
	Revenue		Improve your top and bottom-line revenue by improving customer experience, providing the right data to decision makers, speeding up data centric projects and collaboration across data teams and business.
	Productivity		When data is accurate and complete, there are fewer errors and rework in processes, leading to cost savings. Time spent correcting bad data can be redirected to more productive activities.

CAPABILITIES

AI Powered

Automatically generates metrics with AI and machine learning to observe and report anomalies in production data.

APIs for CI/CD

Engineered with API first approach to seamlessly integrate in CI/CD pipeline such as Jenkins, Azure Pipelines, Bamboo and GIT repository.

Performance & Scalability

iceDQ does not use database for processing instead it use Java processing for high performance and low latency. It also has a Spark for scaling to petabytes of data.